| 基于模糊支持度采样的粒子滤波算法 |
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| 引用本文： | 李小偎,胡振涛,潘泉,张洪才.基于模糊支持度采样的粒子滤波算法[J].计算机测量与控制,2012,20(1):190-192. |
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| 作者姓名： | 李小偎 胡振涛 潘泉 张洪才 |
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| 作者单位： | 1. 西北工业大学自动化学院,陕西西安,710072
2. 河南大学计算机与信息工程学院,河南开封,475004 |
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| 基金项目： | 国家自然科学基金重点项目，国家自然科学基金 |
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| 摘 要： | 针对粒子滤波中重采样导致粒子多样性减弱造成的滤波精度下降问题,给出了一种基于模糊支持度采样的改进粒子滤波算法;该算法在重采样过程后,首先根据MCMC(Markov Chain Monte Carlo)原理抽取候选粒子,然后依据重采样粒子和候选粒子自身数据中的蕴含信息,并结合模糊理论构建支持度函数和支持度矩阵,以充分地提取数据中的有效信息,在增强粒子多样性的同时实现其对于粒子的优选;最后仿真结果表明,该算法可有效地提高对于系统状态的估计精度。
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| 关 键 词： | 粒子滤波 目标跟踪 模糊支持度 支持度函数 |
An Improved Particle Filtering Algorithm Based on Fuzzy Support Degree Sampling |
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| Li Xiaowei
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Hu Zhentao
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Pan Quan
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Zhang Hongcai.An Improved Particle Filtering Algorithm Based on Fuzzy Support Degree Sampling[J].Computer Measurement & Control,2012,20(1):190-192. |
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| Authors: | Li Xiaowei Hu Zhentao Pan Quan Zhang Hongcai |
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| Affiliation: | 1(1.College of Automation,Northwestern Polytechnical University,Xi’an 710072,China; 2.College of Computer and Information Engineering,Henan University,Kaifeng 475001,China) |
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| Abstract: | By the analysis that the degeneracy of particles diversity in the course of re-sampling causes the descent of filtering precision,an improved particle filtering algorithm based on fuzzy support degree sampling is proposed.After the re-sampling process,the new algorithm firstly extracts candidate particles based on Markov Chain Monte Carlo principle,and then,according to the information implicated from the re-sampling and candidate particles and fuzzy theory establishes support degree function and matrix to make fully use of effective information.Thereby the increasing of the diversity of particles and the optimizing selection of particles are realized.Finally,simulation results show the method can effectively improve state estimation precision. |
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| Keywords: | particle filtering target tracking fuzzy support degree support degree function |
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